A synthetic data-driven machine learning approach for athlete performance attenuation prediction

A synthetic data-driven machine learning approach for athlete performance attenuation prediction

IntroductionAthlete performance monitoring is effective for optimizing training strategies and preventing injuries. However, applying machine learning (ML) frameworks to this domain remains challenging due to data scarcity limitations. This study extends previous research by evaluating Tabular Varia...

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Bibliographic Details
Main Authors: Mauricio C. Cordeiro, Ciaran O. Cathain, Lorcan Daly, David T. Kelly, Thiago B. Rodrigues
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Sports and Active Living
Subjects:
synthetic data
performance prediction
machine learning
tabular variational autoencoders
athlete monitoring
Online Access:https://www.frontiersin.org/articles/10.3389/fspor.2025.1607600/full
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https://www.frontiersin.org/articles/10.3389/fspor.2025.1607600/full

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